Evidence map›Paper›PMID 38012549›Full record

ArticleBMC public health2023

Association between environmental factors and dengue incidence in Lao People's Democratic Republic: a nationwide time-series study.

Masumi Sugeno, Erin C Kawazu, Hyun Kim, Virasack Banouvong, Nazife Pehlivan, Daniel Gilfillan, Ho Kim, Yoonhee Kim

Abstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Masumi SugenoDepartment of Global Environmental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan.
Erin C KawazuInstitute for Global Environmental Strategies, Hayama, Japan.
Hyun KimSchool of Public Health, University of Minnesota Twin Cities, Minneapolis, USA.
Virasack BanouvongLao PDR Centre for Malariology, Parasitology and Entomology, Vientiane Capital, Lao People's Democratic Republic.
Nazife PehlivanGraduate School of Public Health, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 151-742, South Korea.
Daniel GilfillanFenner School of Environment and Society, Australian National University, Australian Capital Territory, Canberra, Australia.
Ho KimGraduate School of Public Health, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 151-742, South Korea. hokim@snu.ac.kr.
Yoonhee KimDepartment of Global Environmental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan. yoonheekim@m.u-tokyo.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDengue fever is a vector-borne disease of global public health concern, with an increasing number of cases and a widening area of endemicity in recent years. Meteorological factors influence dengue transmission. This study aimed to estimate the association between meteorological factors (i.e., temperature and rainfall) and dengue incidence and the effect of altitude on this association in the Lao People's Democratic Republic (Lao PDR).

methodsWe used weekly dengue incidence and meteorological data, including temperature and rainfall, from 18 jurisdictions in Lao PDR from 2015 to 2019. A two-stage distributed lag nonlinear model with a quasi-Poisson distribution was used to account for the nonlinear and delayed associations between dengue incidence and meteorological variables, adjusting for long-term time trends and autocorrelation.

resultsA total of 55,561 cases were reported in Lao PDR from 2015 to 2019. The cumulative relative risk for the 90

conclusionsWe found a lagged nonlinear relationship between meteorological factors and dengue incidence in Lao PDR. These findings can be used to develop climate-based early warning systems and provide insights for improving vector control in the country.

Indexed as

DengueWeatherHumansIncidenceLaosRainSoutheast Asian PeopleTemperatureDengueRainfallRisk assessmentTemperatureVector-borne diseases

Identifiers

PMID38012549
PMCPMC10683213

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.